Oct 25, 2026 · 31 min · 12 segments
**What if the biggest challenge in CPQ isn't the configuration engine itself, but getting the right product knowledge into it?** In this episode of the CPQ Podcast, Frank Sohn welcomes back **Kiana…
So now you have introduced something, what you're calling the intelligence platform.
Yeah, so I've, I talked to hundreds of manufacturers and what I came away with, interestingly, even though they're all in different industries, is two things typically hold back the full value of CPQ for them.
The effort that it takes to model their products and then how many people can actually quote them with accuracy.
So, you know, as we know, working with products and doing implementations, building that model out is real work and then maintaining it is also a lot of real work.
And so both of those things depend on a small number of people who understand the product deeply and also understand how to model that knowledge in CPQ.
And so most manufacturers, when we talk to them, is to end up modeling the more straightforward part and leaving the hardest part of their catalog still with engineering.
And then let's say once they get that CPQ rolled out, the same problem, I think, shows up on the sales side.
The right configuration still takes expert time and it can take hours or even weeks in some cases to get a quote out.
So those are the major problems that we're going after, where the intelligence platform helps capture that product knowledge once and then puts it to work on both sides, both on building the model and then selling from it.
And that was one thing I wanted to ask you next, right? So that's about the AI model builder.
That's what you call the administrative side, right? So, and tell me a little bit more about that as well as on the sales side was the AI seller.
Yeah, so AI Model Builder is on the administrative side and it really gets more of a manufacturer's catalog into the configurator much faster.
So whether those are spec sheets, drawings, for example, bill of materials, and then drafts the configurator model from that.
And so the modeling work goes from months of sitting in rooms, pulling knowledge out of people into a few hours of review.
And do you use it internally right now also for customers to bring their products faster into your tool? Yeah.
So now you have introduced something, what you're calling the intelligence platform.
Yeah, so I've, I talked to hundreds of manufacturers and what I came away with, interestingly, even though they're all in different industries, is two things typically hold back the full value of CPQ for them.
The effort that it takes to model their products and then how many people can actually quote them with accuracy.
So, you know, as we know, working with products and doing implementations, building that model out is real work and then maintaining it is also a lot of real work.
And so both of those things depend on a small number of people who understand the product deeply and also understand how to model that knowledge in CPQ.
And so most manufacturers, when we talk to them, is to end up modeling the more straightforward part and leaving the hardest part of their catalog still with engineering.
And then let's say once they get that CPQ rolled out, the same problem, I think, shows up on the sales side.
The right configuration still takes expert time and it can take hours or even weeks in some cases to get a quote out.
So those are the major problems that we're going after, where the intelligence platform helps capture that product knowledge once and then puts it to work on both sides, both on building the model and then selling from it.
And that was one thing I wanted to ask you next, right? So that's about the AI model builder.
That's what you call the administrative side, right? So, and tell me a little bit more about that as well as on the sales side was the AI seller.
Yeah, so AI Model Builder is on the administrative side and it really gets more of a manufacturer's catalog into the configurator much faster.
So whether those are spec sheets, drawings, for example, bill of materials, and then drafts the configurator model from that.
And so the modeling work goes from months of sitting in rooms, pulling knowledge out of people into a few hours of review.
And do you use it internally right now also for customers to bring their products faster into your tool? Yeah.
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